Multi symbol bit detection for SDPSK signals

Description

BACKGROUND OF THE INVENTION

The proposed invention, in general, relates to the demodulation of a symmetrical differential phase shift keying (SDPSK) modulated signal, and specifically relates to an improved method of bit error rate (BER) detection in a SDPSK modulated signal.

The method disclosed in this invention is a technique of improving the BER for the detection of SDPSK modulated signals. The current methods in the art do not yield accurate measurements of BER in SDPSK modulated systems. The method disclosed in this invention gives the same BER at a reduced signal to noise ratio (SNR). The method of improving the detection of SDPSK modulated signals, disclosed herein, can be applied to any communication system using SDPSK modulation.

In the current art for BER estimation in SDPSK modulated signals, the immediate previous bit is used to detect the current bit.

SUMMARY OF THE INVENTION

The proposed invention discloses a method for accurately detecting the current bit in a SDPSK modulated signal at the receiver. The proposed method calculates the current bit from the past-detected bits and the past symbols. Each past symbol estimates the current bit. Each of these estimates is summed up to provide the final estimate of the current bit.

The proposed method for the detection of SDPSK modulated bits improves the bit error rate performance. For example, if the system has a bit error rate of 0.01 at a signal to noise ratio (SNR) of say 6 dB, then the proposed method will achieve a bit error rate of 0.01 at a SNR of 5.4 dB.

One advantage of the proposed method is the improvement in bit error rate (BER) performance.

Another advantage of the proposed method is that, it can be applied to any communication system that uses SDPSK modulation.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A illustrates the graphical representation of bit error rate versus signal to noise ratio at depth 4 and depth 0.

FIG. 1B illustrates the graphical representation of bit error rate versus signal to noise ratio at depth 5 and depth 0.

FIG. 1C illustrates the graphical representation of bit error rate versus signal to noise ratio at depth 10 and depth 0.

DETAILED DESCRIPTION OF THE INVENTION

The method used in this invention considers all previous symbols and bits for the estimation of a current bit in the detection of the symmetrical differential phase shift keying (SDPSK) modulated signal.

The SDPSK modulation scheme is represented by the equation:
S_n=S_n-1*e^(j*Π*bn/2)

where S_n is the current modulated symbol

S_n-1 is the previous modulated symbol

b_n is the current bit (b_n=1 for bit 1, b_n=−1 for bit 0)

where j=√−1 and Π is a transcendental number, equal to approximately 3.142 . . .

The equations listed below substitute S_n-1 for four recursive expressions. By way of example, only four recursive expressions are shown to explain this invention. In actual practice, any number of recursive expressions can be used. Larger the number of recursive expressions used, greater is the improvement in BER performance.
S_n=S_n-1*e^(j*Π*bn/2)
S_n=S_n-2*e^(j*Π*bn/2)*e^{(j*Π*bn−1/2)}
S_n=S_n-3*e^(j*Π*bn/2)*e^{(j*Π*bn−1/2)}*e^{(j*Π*bn−2/2)}
S_n=S_n-4*e^(j*Πbn/2)*e^{(j*Π*bn−1/2)}*e^{(j*Π*bn−2/2)}*e^{(j*Π*bn−3/2)}

Similarly, S_n can be derived as a function of any of the previous bits. The following four equations are derived from the above four equations respectively.
e^(j*Π*bn/2)=S_n*conj(S_n-1)   (a)
e^(j*Π*bn/2)=S_n*conj(S_n-2)*e^{(j*Π*bn−1/2)}   (b)
e^(j*Π*bn/2)=S_n*conj(S_n-3)*e^{(j*Π*bn−1/2)}*e^{(j*Π*bn−2/2)}   (c)
e^(j*Π*bn/2)=S_n*conj(S_n-r)*e^{(j*Π*bn−1/2)}*e^{(j*Π*bn−2/2)}*e^{(j*Π*bn−(r−1)/2)}   (d)
Applying Eulers theorem to the equation e^(j*Π*bn/2)=S_n*conj(S_n−1), we derive:
Cos (Π/2.b_n)+j Sin (Π/2.b_n)=S_n*conj(S_n-1)
Applying Eulers theorem and summing the left hand side and right hand side of equations (a), (b), (c) and (d),
(Cos(Π/2.b_n)+j Sin(Π/2.b_n))*r=S_n*conj(S_n-1)+S_n*conj(S_n-2)*e^{(j*Π*bn−1/2)}+ . . . +S_n*conj(S_n-2)*e^{(j*Π*bn−(r−1)/2)})   (e)
b_n can assume only one of the two values, viz. −1 or +1.
Therefore, for b_n=1, Cos (Π/2.b_n)=0 and Sin (Π/2 b_n)=r
and for b_n=−1, Cos (Π/2.b_n)=0 and Sin (Π/2 b_n)=−r
The imaginary part on the left side should be equal to the imaginary part on the right side of equation (e), while the real part on the left side should be equal to the real part on the right side.
Sign of the imaginary part on the left side should be equal to the sign of the imaginary part on the right side of the equation (e).

Hence, bn is given by the sign of the imaginary part on the right hand side of equation (2)
b_n=sign(imag(S_n*conj(S_n-1)+ . . . +S_n*conj(S_n-(r-1))))
It can be observed from the above equations that multiple estimates for b_n can be derived.

The sum of all the above estimates provides an accurate assessment of the current bit b_n, represented by the following equation:
b_{n—estimated}=[S_n*conj(S_n-1)+S_n*conj(S_n-2)*e^{(j*Π*bn-1/2)}+S_n*conj(S_n-3)*e^{(j*Π*bn-1/2)}*e^{(j*Π*bn-2/2)}+S_n*conj(S_n-4)*e^{(j*Π*bn-1/2)}*e^{(j*Π*bn-2/2)}*e^{(j*Π*bn−3/2)}]
The current bit is calculated by the formula:
Bit=sign(imag(b_{n—estimated}))
wherein, sign (x)=1 if x>0 and sign (x)=−1 if x<0
imag(x) is the imaginary part of the complex number x.

FIG. 1A illustrates the graphical representation of bit error rate versus signal to noise ratio in depth 4 by implementing the method presented in this invention. Depth is the number of past bits that are used to estimate the current bit. From the graph, it is found that the plots for depth 0 101 and depth 4 102 at an SNR of 6 dB, the bit error rates are approximately 0.009 and 0.006 respectively.

FIG. 1B illustrates the graphical representation of bit error rate versus signal to noise ratio in depth 5 by implementing the method presented in this invention. From the graph, it is found that the plots for depth 0 101 and depth 5 103 at an SNR of 6 dB, the bit error rates are approximately 0.009 and 0.0055 respectively.

FIG. 1C illustrates the graphical representation of bit error rate versus signal to noise ratio in depth 10 by implementing the method presented in this invention. From the graph, it is found that the plots for depth 0 101 and depth 10 104 at an SNR of 6 dB, the bit error rates are approximately 0.009 and 0.005 respectively.

It is observed from FIG. 1A, FIG. 1B and FIG. 1C that as the depth increases, i.e., as the number of past bits used in BER estimation is increased, the BER performance improves progressively.